Lightweight convolutional neural network models for semantic segmentation of in-field cotton bolls-Reference-Cited by-同舟云学术

Lightweight convolutional neural network models for semantic segmentation of in-field cotton bolls

Published:2023-06 Issue: Volume:8 Page:1-19
ISSN:2589-7217
Container-title:Artificial Intelligence in Agriculture
language:en
Short-container-title:Artificial Intelligence in Agriculture

Author:

Singh Naseeb,Tewari V.K.,Biswas P.K.,Dhruw L.K.

Funder

Indian Institute of Technology Kharagpur

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Agricultural and Biological Sciences,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference95 articles.

1. Fine-tuning convolutional neural network with transfer learning for semantic segmentation of ground-level oilseed rape images in a field with high weed pressure;Abdalla;Comput. Electron. Agric.,2019

2. Learning semantic graphics using convolutional encoder–decoder network for autonomous weeding in paddy;Adhikari;Front. Plant Sci.,2019

3. Plant leaf disease classification using EfficientNet deep learning model;Atila;Ecol. Inform.,2021

4. Semantic segmentation: a modern approach for identifying soil clods in precision farming;Azizi;Biosyst. Eng.,2020

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